Industrial Crops & Products 126 (2018) 261–271

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Industrial Crops & Products

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LC–MS/MS-based chemometric analysis of phytochemical diversity in 13 T spp. (): Correlation to their in vitro antimicrobial and in silico quorum sensing inhibitory activities ⁎ Seham S. Elhawarya, Inas Y. Younisa, , Mahitab H. El Bishbishyb, Amira R. Khattabc a Department of Pharmacognosy, Faculty of Pharmacy, Cairo University, Cairo 11562, Egypt b Department of Pharmacognosy, Faculty of Pharmacy, MSA University, Giza 12585, Egypt c Department of Pharmacognosy, Division of Pharmaceutical Sciences, College of Pharmacy, Arab Academy for Science, Technology and Maritime Transport, Alexandria 1029, Egypt

ARTICLE INFO ABSTRACT

Keywords: Thirteen Ficus species, family Moraceae, were profiled via HPLC-ESI-MS/MS. About 35 metabolites were ten- Fig tatively identified, for the first time, belonging to various classes including flavonoids (flavonols, flavanols, Moraceae flavanonols, flavones, flavanones), flavonolignans, anthocyanins and hydroxycinnamic acids derivatives). We Principal component analysis herein also report three species, viz. Ficus auriculata, Vahl. and Ficus trigonata L., with promising Hierarchical clustering analysis antimicrobial activity for the management of the infectious diseases associated with the tested food-borne and Docking spoilage microorganisms using agar well diffusion assay. The compositional variabilities existing among the studied species in correlation to their antimicrobial activities were explored using different chemometric tools. From the Orthogonal Projection to Latent Structures (OPLS) regression model, a correlation between the ob- served antimicrobial activity and the abundant Ficus phytoconstituents viz. quercetin-3-glucoside, kaempferol-3- O-rutinoside, kaempferol-3-O-glucoside, rutin and chlorogenic acid, was evidenced. By showing promising in silico anti-quorum sensing efficacy, these phytoconstituents could represent a promising set of natural hencesafe antimicrobial agents.

1. Introduction drugs and the emergence of multidrug-resistant microbial strains (Rashed and Butnariu, 2014). The infectious diseases could be classified Ficus genus is one of the most diverse genera belonging to Moraceae into three major classes; according to Infectious Disease Prevention Act family, constituting more than 800 species distributed in tropical and of (Class A, B and C based on their legal managements), or based subtropical regions and collectively known as fig . Among the on their transmission routes as being respiratory, digestive, contact, notorious species of Ficus are Ficus carica, Ficus religiosa L., water-, blood- or vector-borne infections (Liu et al., 2015). That is why Roxb. ex Hornem., Ficus benghalensis L. (the ) and Ficus a global concern is being directed now towards developing safer natural racemosa L. (Farag et al., 2014a). alternatives for the effective management of the infectious diseases Compared to the , barks and roots of figs, the have re- caused by resistant microbes (Aqil and Ahmad, 2003). ceived little research interest. Among the phytochemicals identified in Ethnobotanically-driven bioactives have been recognized as poten- figs are flavonoids, lignans, coumarins, terpenoids, alkaloids, sterols, tial sources of novel antimicrobial agents with diverse chemical struc- and cinnamic and caffeic acid derivatives (Kuo and Li, 1997; Wu et al., tures. Most of the detected phenolic compounds in Ficus spp. have a 2002; Almahyl et al., 2003). Various health benefits such as anti- well-reported antimicrobial activity against Staphylococcus aureus, oxidant, antimicrobial, antidiabetic, anticancer and antirheumatic ac- Escherichia coli, and Pseudomonas aeruginosa, while no significant anti- tivities have been attributed to most of the reported Ficus spp. bacterial activity against Klebsiella pneumoniae and Streptococcus pneu- (Ramadan et al., 2009; Shi et al., 2011). moniae, methicillin-resistant S. aureus nor antifungal activity against Infectious diseases represent one major health problem leading to Candida albicans (Aqil and Ahmad, 2003; Murti and Kumar, 2011). around fifty thousand deaths daily due to shortcomings of the available The current study aimed to profile the metabolites in thirteen under-

⁎ Corresponding author. E-mail address: [email protected] (I.Y. Younis). https://doi.org/10.1016/j.indcrop.2018.10.017 Received 3 August 2018; Received in revised form 11 September 2018; Accepted 5 October 2018 0926-6690/ © 2018 Published by Elsevier B.V. S.S. Elhawary et al. Industrial Crops & Products 126 (2018) 261–271 exploited Ficus species, and explore their antimicrobial activity against (OPLS), was performed to highlight correlation existing between the X a number of pathogenic microorganisms to spot the light on the species variables (relative abundance of base peak of the identified metabolites that could be used as safer alternative to synthetic anti-microbial by HPLC-ESI-MS/MS) and Y variables (antimicrobial activity). Variable agents. In addition, quorum sensing inhibition activity was screened for Importance in Projections (VIP) and permutation analysis were carried the phytochemicals present most abundantly in Ficus species that out to further confirm the significance and validity of the OPLS model, showed promising anti-microbial activities. respectively. Data were analyzed using The SIMCA-P software (Version 14.0, Umetrics, Umeå, Sweden). 2. Experimental 2.5. Molecular docking 2.1. material and extraction procedures Molecular modeling studies were carried out using Molecular Leaves of 13 Ficus species under investigation were provided from El Operating Environment (MOE, 10.2008) software. All minimizations Orman Botanical Garden, Giza, Egypt during March 2016 and identified were performed with MOE until an RMSD gradient of 0.1 kcal by Dr. Mohamed El-Gebaly (National Research Institute, Dokki, Giza, mol−1 Å−1 with MMFF94x force field and the partial charges were Egypt). Voucher specimens of all the species were deposited in automatically calculated. The X-ray crystallographic structure of Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Pseudomonas aeruginosa LasR quorum-sensing signaling receptor co- Cairo, Egypt. Details about the collected samples, their respective codes crystallized with an autoinducer mimic “2,4-dibromo-6-[[(2-ni- and voucher numbers are depicted (Table S1). The Fresh leaves (500 g) trobenzoyl)amino]methyl]phenyl-2-chlorobenzoate (TX1)” [EC50 = were air dried at room temperature then, ground into fine powder. 28 nM] (PDB ID: 3IX4) was downloaded from the protein data bank via 100 g of each specimen were extracted by ethanol 70% till exhaustion, http://www.rcsb.org/ (Zou and Nair, 2009). Chains A–G and water solid residues were removed by filtration (Pentea et al., 2015). The molecules were removed and only chain H was kept. Then, the protein ® solvent was evaporated at 45 °C using rotary evaporator (Buchi R-300, was prepared for docking study using Protonate 3D protocol in MOE USA) and stored at 20 °C until further use. with default options. The co-crystalized ligand was used to define the binding site for docking. Triangle Matcher placement method and 2.2. High resolution HPLC-ESI-MS/MS analysis London dG scoring function were used for docking. Docking setup was first validated by re-docking of the co-crystallized ligand (TX1) inthe HPLC-ESI-MS/MS analysis was performed according to the method vicinity of the binding site of the receptor with energy score described in (Elshafie et al., 2017). In brief, a sample of 10 μL of each (S) = −16.68 kcal/mol and RMSD of 0.798 Å and with the ability to Ficus species leaves extract was separately injected using ThermoQuest reproduce all the key interactions accomplished by the co-crystallized autosampler surveyor (Thermo Electron Corporation, Waltham, MA, ligand with the key amino acids in the binding site through H-bonding USA) into Thermo Finnigan LC system (Thermo Electron Corporation, with Tyr56, Asp73 and Ser129. The validated setup was then used in Waltham, MA, USA) coupled with Zorbax Eclipse XDB-C18 predicting the ligands receptor interactions at the binding site for the (4.6 × 150 mm, 3.5 μm, Agilent, Santa Clara, CA, USA). The elution compounds of interest. was performed at ambient temperature using a mobile phase consisting of water and acetonitrile enriched with 0.1% formic acid in gradient 2.6. Statistical analysis elution from 5% to 30% acetonitrile for 120 min at a flow rate of 1 ml/ min with splitting ratio of 1:1 before the ESI source. The ESI source The values of the antimicrobial activity are presented as the (Thermo Quest) was operated in the negative mode with full scan mode means ± standard deviation. Significant differences between the Ficus from 50 to 2000 m/z. samples were assessed by one-way analysis of variance (ANOVA) fol- lowed by Tukey post hoc-test test. A value of p < 0.05 was considered 2.3. In vitro antimicrobial assay significant.

In vitro antimicrobial activity of Ficus spp. under study were de- 3. Results and discussion termined against several pathogenic food-borne and spoilage micro- organisms including Escherichia coli (ATCC 25955), Bacillus subtilis 3.1. Identification of major metabolites in Ficus species via HPLC-ESI-MS/ (NRRL B-543), Staphylococcus aureus (RCMB 010010), Candida albicans MS (ATCC 10231), Aspergillus fumigatus (RCMB 002008), Streptococcus mutants (ATCC 25175), Salmonella typhimurium (ATCC 14028), The proper separation and identification of bio-active sec- Klebsiella pneumonia (ATCC 13883) were used as the tested micro- ondary metabolites is a crucial step in their employment as potential organisms. Bacteria, yeasts and moulds were maintained on nutrient therapeutic agents (Butu et al., 2014). Accordingly, the leaves extracts agar (NA), yeast extract peptone dextrose agar (YPD) and potato dex- from Ficus species were subjected to hyphenated chromatographic and trose agar (PDA) culture medium at 4 °C, respectively. All the tested mass spectrometric analyses, where, chromatographic fingerprints of microorganisms were sub-cultured on their respective media, at 37 °C the thirteen extracts were obtained using HPLC-ESI-MS/MS and a re- for bacteria and at 28 °C for yeasts and moulds for 24 h. All tested presentative chromatogram of the leaves extract of F. religiosa L. is microorganisms were obtained from Regional Center for Mycology and depicted in Fig. 1. The identities, UV characteristics, and observed Biotechnology unit (RCMB), Cairo, Egypt. Agar well diffusion method molecular and fragment ions for individual components are presented was carried out as described in (Elshafie et al., ).2018 (Table 1) and the identified compounds structures are presented (Fig. 2). 2.4. Multivariate data analysis The UV absorbances of the compounds were detected using Photo Diode Array detector (PDA), which was considered for proper com- An exploratory analysis of the data, composed from relative abun- pounds assignments. The major class of compounds identified in Ficus dance of base peaks of the identified metabolites by HPLC-ESI-MS/MS, extracts is flavonoids, showing characteristic UV absorbances at was carried out using principal component analysis (PCA) and hier- 240–290 nm (for Band II), due to ring A conjugation. However, some archical clustering analysis (HCA), to display the metabolic variabilities flavonoids showed absorbances at 300–550 nm (for Band I), whichre- among Ficus spp. under study. On the other hand, supervised pattern presented conjugated B and C rings (Santos-Buelga et al., 2003). The recognition method, viz. orthogonal projection to latent structures number of hydroxyl substitutions and the glycosylation of the

262 S.S. Elhawary et al. Industrial Crops & Products 126 (2018) 261–271

Fig. 1. A representative HPLC-ESI-MS/MS chromatogram of the leaves extract of F. religiosa L. flavonoids account for the locations of band I and II maxima, andhence (Mena et al., 2012; Savić et al., 2014). Catechin glucoside was also compound identification. detected with [M−H]− of 448.7867 and MSn fragment with m/z A total of 35 metabolites were tentatively assigned and character- 287.06 (Ammar et al., 2015a). ized on the basis of their retention times, molecular formulae, mole- cular mass of parental ion and MS/MS fragmentation patterns com- 3.1.4. Characterization of flavanones pared to the data previously reported in literature. Naringin and its aglycone “naringenin” were identified by their With the optimized LC and MS conditions, different subclasses of characteristic MS/MS fragment with m/z 271 and [M−H]− at m/z flavonoids were detected including flavonols, flavanonols, flavanols, 579.1672 and 271.2468, respectively (Belhadj Slimen et al., 2017). flavones and flavanones, in addition to flavonolignan, anthocyanins Another flavanone, 5,7,8,4′-tetrahydroxyflavanone (carthamidin), was and hydroxycinnamic acids derivatives. also identified (Wang et al., 2008).

3.1.1. Characterization of flavonols 3.1.5. Characterization of flavanonols, flavonolignans and anthocyanins Quercetin, kaempferol and isorhamnetin glycosides were the major Furthermore, taxifolin (dihydroquercetin) was the only flavanonol flavonols identified in Ficus spp. Quercetin O-glycosides such as, quer- identified in the studied Ficus species showing ([M−H]− of 302.5275 cetin-3-O-glucoside, quercetin 3-sambubioside, quercetin-3-O-rutino- and MS/MS fragment ion with m/z at 285.13), along with the flavo- side (rutin), quercetin glucoside-O-rutinoside, quercetin-3-O-galacto- nolignan “cinchonain Ia (isomer)” showing m/z at 451.0913 and MS/ side (hyperoside) and its dimer (the absolute configuration of the dimer MS with m/z at 341.16 (Ammar et al., 2015b; Elsadig Karar and linkage is uncertain), showing characteristic m/z at 301 and their re- Kuhnert, 2016). However, procyanidin B1 was the only anthocyanin spective molecular weights were recorded (Table 1). Three kaempferol identified with its deprotonated molecular ion peakat m/z 577.19 and O-glycosides namely, kaempferol hexoside rhamnoside, kaempferol-3- MS/MS fragment ion with m/z at 425.07 (Simirgiotis, 2013). O-rutinoside (nicotiflorin) and kaempferol 7-O-glucoside showed m/z at 285 which is characteristic for kaempferol derivatives (Ammar et al., 3.1.6. Characterization of hydroxycinnamic acids derivatives 2015a; Bakr and El Bishbishy, 2016; Elsadig Karar and Kuhnert, 2016). Five peaks were identified as corresponding to hydroxycinnamic n Additionally, one isorhamnetin-3-O-rutinoside (m/z 622.8761 and MS acids derivatives. Ficus species was found to contain chlorogenic and with m/z at 315.16) was also found (Ammar et al., 2015a). cryptochlorogenic acids having [M−H]− at m/z 353. Although they both shared the same product ion at m/z 191, cryptochlorogenic acid 3.1.2. Characterization of flavones showed further fragment at m/z 173.57, which is used to differentiate C-linked flavone glycosides were reported as the major formof between both compounds according to (Zhang et al., 2015). 3,5-Di- flavones present in the studied Ficus species (Farag et al., 2014a; Omar caffeoylquinic acid [M−H]− at m/z 515, 3,4-dimethyl-caffeic acid et al., 2011). Different apigenin and luteolin C-glycosides were identi- [M−H]− at m/z 207 and cis-5-O-p-coumaroylquinic acid [M−H]− at fied, viz. apigenin 6-C-xyloside-8-C-glucoside (vicenin 1), apigenin-6,8- m/z 337 were also detected (Falcão et al., 2013; Elsadig Karar and C-diglucoside (vicenin 2), apigenin 8-C-xyloside-6-C-glucoside (vicenin Kuhnert, 2016). 3), apigenin-8-C-glucoside-4”-O-glucoside (vitexin 4”-O- glucoside), The presence of C-linked flavone glycosides is well-evidenced by the apigenin-8-C-glucoside-2”-O-rhamnoside (vitexin-2”-O-rhamnoside), rigid C-C linkage, which resisted the fragmentation, as revealed in the apigenin-6-C-ß-D-glucopyranosyl-8-C-α-L-arabinopyranoside (schafto- fragmentation patterns of different apigenin and luteolin C-glycosides side) and its isomer isoschaftoside, as well as, orientin, luteolin-8-C- identified. On the other hand, O-glycosylated flavonoids are more glucoside (Zhang et al., 2005; Negri et al., 2012; Es-Safi and Gómez- susceptible to fragmentation which is started by the cleavage of the Cordovés, 2014; Farag et al., 2014b; Zhu et al., 2015; Elsadig Karar and glycosidic linkage, followed by loss of the sugar moieties and retaining Kuhnert, 2016). Besides, two O-linked flavone glycosides were identi- the charge on the aglycones (Plazonić et al., 2009). fied as apigenin-7-O-neohesperidoside (rhoifolin) (Zhang et al., 2005). 3.2. Antimicrobial activity of Ficus spp 3.1.3. Characterization of flavanols Three compounds belonging to flavanols were identified, viz. A substantial public health concern now is directed towards the (+)-catechin and (+)-epicatechin, which yielded deprotonated mole- food-borne illness arising from contaminated foods with pathogenic cules at m/z 289 with a characteristic MSn fragment at m/z 245 and bacteria and moulds. Accordingly, there is a worldwide preference to they were differentiated from each other based on their retention times incorporate natural, safe and healthier alternatives to chemical

263 ..Ehwr tal. et Elhawary S.S. Table 1 Tentative identification of secondary metabolites in ethanoic extracts of the studied Ficus spp. using HPLC-ESI-MS/MS; (++), (+) and (-) indicate the high abundance, moderate abundance and absence of the metabolites.

No. UV max [M−H]− (m/ MSn product ions Elemental Identification Distribution in Ficus species z) Composition F_BG F_BN F_MY F_AF F_PY F_RA F_LU F_AU F_TR F_SP F_NIT F_VER F_LS

I. Flavonoids–flavonols 1 345 593.8448 503.2, 473.19, 339.44, 285.45 C27 H30 O15 Kaempferol hexoside rhamnoside –––––– ++ –––––– 2 256, 352 771.2313 609.23, 463.15, 301.18, 255.27 C33 H40 O21 Quercetin glucoside-O-rutinoside ––– + –––– + –– + ++ 3 255, 358 608.7215 427.00, 343.07, 301.15, C27 H30 O16 Quercetin-3-O-rutinoside (Rutin) – + – ++ – + – + + –––– 271.29, 179.16 4 256, 353 594.5559 300.2, 271.41, 255.43 C26 H28 O16 Quercetin 3-sambubioside –––––– + + –– ++ – 5 255, 353 927.9919 602.35, 463.14, 300.14 C42 H40 O24 Hyperoside Dimer ––––––––––– ++ – 6 255, 359 463.0731 301.16, 179.14, 151.1 C21 H20 O12 Hyperoside –––––– ++ –––––– 7 268, 344 593.1304 447.12, 357.16, 327.07, 285.17 C27 H30 O15 Kaempferol-3-O-rutinoside (Nicotiflorin) ––– ++ – ++ ++ + + + ––– 8 253, 346 463.4985 343.10, 301.17, 179.19 C21 H20 O12 Quercetin-3-O-glucoside (Isoquercitrin) ––––– + + ++ + –––– 9 264, 346 447.2246 447.23, 284.16, 174.24 C21 H20 O11 Kaempferol 7-O-glucoside –––––– ++ – + –––– 10 271, 354 622.8761 447.04, 387.18, 315.16, C28 H32 O16 Isorhamnetin-3-O-rutinoside – ++ –– + ––– + –––– 271.27, 178.52

II. Flavonoids–flavanols 11 279 288.9968 289.00, 271.15, 245.20, C15 H14 O6 Catechin (+) ––– + – + ++ – + –––– 205.30, 179.27 12 278 289.1651 245.19, 205.25, 203.38, C15 H14 O6 Epicatechin (+) ––– ++ – + – + –––– 187.38, 179.23 13 287 448.7867 431.10, 402.95, 287.06, 269.24 C21 H24 O11 Catechin glucoside –– ++ ––––– + –– + – III. Flavonoid–flavanonols 264 14 287, 334 302.3275 302.33, 285.13, 125.17 C15 H12 O7 Taxifolin (Dihydroquercetin) ––––– + + – ++ –– + – IV. Flavonoids–flavones 15 271, 330 563.1572 473.2, 443.17, 353.28 C26 H28 O14 Apigenin 8-C-xyloside-6-C-glucoside –– ++ – ++ – ++ –– ++ –– + (Vicenin 3) 16 272, 334 563.2086 545.22, 503.19, 473.22, C26 H28 O14 Isoschaftoside (isomer of Schaftoside) –––– ++ + – + ––––– 443.19, 383.29, 353.28 17 271, 326 593.3064 503.19, 473.22, 383.38, 353.39 C27 H30 O15 Apigenin-6,8-C-diglucoside –– + + ++ –––––––– (Vicenin 2) 18 272, 338 563.1648 545.19, 503.19, 473.2, 443.24, C26 H28 O14 Apigenin 6-C-ß-D-glucopyranosyl-8-C-α-L- –––– ++ – + – + ++ ––– 383.27, 353.24 arabinopyranoside (Schaftoside) 19 271, 328 563.4967 473.2, 443.24, 383.34, 353.32 C26 H28 O14 Apigenin 6-C-xyloside-8-C-glucoside –––– ++ –––– + – + – (Vicenin 1) 20 270, 344 446.9125 357.25, 327.43 C21 H20 O11 Luteolin-8-C-glucoside (Orientin) –– + + ++ – + –– + ++ –– 21 270, 337 593.2007 413.21, 293.62 C27 H30 O15 Vitexin-4″-O- glucoside ––––––––– + + ––

22 265, 344 576.4744 457.1541, 413.1310, 293.3108 C27 H30 O14 Vitexin-2″-O- rhamnoside ––– + –– ++ –– + –– + Industrial Crops&Products126(2018)261–271 23 267, 326 431.3082 341.18, 311.20 C21 H20 O10 Apigenin 8-C-glucoside (Vitexin) –– + + + + ++ + + ++ ––– 24 266, 336 431.1666 413.17, 341.21, 311.23, C21 H20 O10 Apigenin 6-C-glucoside (Isovitexin) –– ++ ++ + + + + + + ––– 283.69, 191.29 25 272 576.6233 401.76, 293.04, 269.24 C27 H30 O14 Apigenin 7-O-neohesperidoside (Rhoifolin) ––––––––– + ++ + – V. Flavonoids–flavanones 26 288 286.5690 269.15, 259.18, 243.41, 219.31 C15 H12 O6 5,7,8,4′-tetrahydroxyflavanone (Carthamidin) – – – – + + – – ++ – +– 27 281 579.1672 271.14, 177.29 C27 H32 O14 Naringin – ++ – – + – – ++ – ++ – – – 28 287 271.2468 271.25, 253.37, 232.70, 225.43 C15 H12 O5 Naringenin – + – – – – – – + ++ – – – VI. Flavonolignan 29 279 451.0913 341.16, 287.25, 217.28, 161.44 C24 H20 O9 Cinchonain Ia (isomer) – – – – ++ + – – – + – – – VII. Anthocyanins 30 279 576.7777 451.12, 425.07, 407.25, 289.18 C30 H26 O12 Procyanidin B1 – – – ++ + – + – – ++ – – – (continued on next page) S.S. Elhawary et al. Industrial Crops & Products 126 (2018) 261–271

L.; preservatives in food products (Serra et al., 2008). From that context, – we screened the antibacterial and antifungal potential of the thirteen Ficus species under study against a wide range of pathogenic and food

++ borne microbes enlisted in Section 2.3 of experimental. The results of the in vitro antimicrobial activity are summarized (Table 2), which highlighted that “F. auriculata L. (F_AU)” is possessing (F_AU ) F.auriculata the potent antifungal activity against A. fumigatus among the other Ficus

–––––––––––– spp., even exceeding that of ketoconazole (the positive control). It also Vahl.; showed a moderate antibacterial activity against S. aureus, which is

++ ++ ++ followed by the observed activity of the other two Ficus species “F. lutea Vahl. (F_LU) and F. trigonata L. (F_TR)”. The latter species was the most effective in inhibiting the growth of B. subtilis, but with a lower activity as compared to the control drug “gentamycin”. ––––––– –––– The potentials of antifungal agents require the evaluation of their

Roxb.; ( F_LU) F. lutea mode of action, activity spectrum and minimum fungicidal concentra-

––– tion (Bagiu et al., 2012). Herein, the highest antifungal activity against C. albicans among all the studied Ficus species was observed with F.

++ + + + pyriformis Hook. & Arn H (F_PY), which also prevented the growth of E. F. racemosa coli, however the activity was less potent than that of the positive – + +–––––––– ++

species controls.

(F_RA ) The rest of the Ficus species varied in their antibacterial activities Ficus ++ ++ against Gram positive and negative bacteria with no or diminished activity against the tested fungi.

– Although, the antimicrobial activity of many plants from this taxon

L. has been widely explored to the best of our knowledge, the anti- ––––+ ––––––––– Distribution in F_BG F_BN F_MY F_AF F_PY F_RA F_LU F_AU F_TR F_SP F_NIT F_VER F_LS Hook. & Arn H.; microbial activity of the two plants “F_AU” and “F_LU” is being reported for the first time. These findings provided an evidence that both plants

F. religiosa could provide potential sources of new natural antimicrobial agents for the management of infections associated with the studied microbes and F. pyriformis safer alternatives to chemical preservatives in food industry. A.; ( F_LS ) (F_PY) 3.3. Multivariate data analysis of Ficus spp F. virens G. Don.; 3.3.1. Exploratory compositional variability using PCA and HCA The metabolic variability of the different Ficus species as analyzed afzelii ( F_VER )

F . by HPLC-ESI-MS/MS was explored using two unsupervised methods namely principal component analysis (PCA) and hierarchical cluster

nitida; analysis (HCA).

var. PCA algorithm is employed to achieve unbiased dimensionality re- cis-5- O - p -Coumaroylquinic acid cis-Cryptochlorogenic acid Chlorogenic acid 3,4-Dimethyl-caffeic acid 3,5-Dicaffeoylquinic acid Identification duction, providing an informative first look at the compositional dif- ferences between the samples. The established model (Fig. 3A & B), resulted in the formation of two orthogonal PCs, which explained 62% of the total variability among the Ficus samples, i.e., PC1, accounted for 8 9 9 4 12 F. microcarpa Heyne Ex. Roth.; ( F_AF) O O O O O 41% of the variance versus 21% for PC2. 18 18 18 14 24

H H H H H The PCA score plot (Fig. 3A) showed that “F_TR” was remotely 16 16 16 11 25 C Elemental Composition positioned, along the positive side of PC1, from the other Ficus samples, which could be ascribed to their variable metabolic make up. The F. mysorensis loading plot (Fig. 3B) pointed out to the metabolites, having a positive effect on PC1, which contributed the most to such distant segregations

(F_MY ) as being cis-5-O-p-coumaroylquinic acid, taxifolin (dihydroquercetin), 163.07 , 119.24 C L.; 5,7,8,4′-tetrahydroxyflavanone (carthamidin), 3,4-dimethyl-caffeic Mildbr. & Burret.; ( F_NIT ) acid and quercetin glucoside-O-rutinoside. Those metabolites appeared to be more abundant in “F_TR”. PCA modeling was not efficient in product ions

n providing a clear discrimination between the studied Ficus species. The F. benjamina MS 207.18 , 179.18, 161.32, 135.35 C 191.20 , 179.40, 173.57, 135.47191.2 , 179.38, C 161.49 353.25 , 335.59, 267.66, 161.52 C same data matrix was subjected to HCA analysis, another unsupervised

F. spragueana pattern recognition method but with different graphical representation. (m/ (F_BN ) The HCA-driven dendrogram (Fig. 3C) portrayed three main clus- − L; ters; cluster “I”, encompassed only the most variant sample “F_TR”,

L.; ( F_SP ) cluster “II” included three Ficus samples namely; F. microcarpa var. ni- z) tida (F_NIT), F. pyriformis Hook. & Arn H “F_PY” and F. spragueana Mildbr. & Burret. (F_SP), whereas the rest of the samples were grouped

F. benghalensis altogether in the third cluster “III”, which is indicative to their similar ( continued ) F. trigonata metabolic composition matrix. 34 281,322 207.1835 3233 289, 324 323 352.6999 35 273, 329 352.7542 515.3197 No. UV max [M−H] VIII. Hydroxycinnamic acids and derivatives 31 312 336.8221 191.20, 173.17, (F_BG) ( F_TR ) – Values in bold represent the base peak. Table 1 –

265 S.S. Elhawary et al. Industrial Crops & Products 126 (2018) 261–271

Fig. 2. The structure of the major metabolite classes identified using HPLC-ESI-MS/MS in the studied Ficus spp., numbered as listed (Table 1).

3.3.2. Relationship between Ficus metabolites and antimicrobial activity and their phytochemical constituents, which is illustrated in the form of a using OPLS biplot (an amalgamation of the information revealed by both the score OPLS regression analysis was applied to explore the correlations be- and loading plots). The model was validated using 100 random permu- tween the antimicrobial activities of the thirteen Ficus species under study tations and showed a significant performance with goodness of model fit

266 ..Ehwr tal. et Elhawary S.S. Table 2 Antimicrobial activity of Ficus spp.

Micro-organism Strain code Inhibition zone (mm)

F_BG(a) F_BN(b) F_MY(c) F_AF(d) F_BI(e) F_RA(f) F_LU(g)

A. fumigatus RCMB 002008 NAg,h,j,m NAg,h,j,m NAg,h,j,m NAg,h,j,m NAg,h,j,m NAg,h,j,m 13 ± 1.0 a-f,h,I,k-m C. albicans ATCC 10231 NAc-f NAc-f 10.83 ± 0.73a,b, d-m 12 ± 0.5a-d,f-I-m 13.23 8.3 NAc-f ± 0.25 a,b,c,f-m ± 0.17a-e,g-m S. mutants ATCC 25175 14.2 ± 0.26b-d,g-m 10.2 ± 0.2 a,c-m 11.13 ± 0.15 a,d-m NAa,b,c,e,f,h,k,l,m 7.1 ± 0.1 13.23 ± 0.25 b-e,g-m NA a,b,c,e,f,h,k-m a,b,c,d,f,g,h,I,j,l S. aureus RCMB 010010 NAg-m NAg-m NAg-m NAg-m NAg-m NAg-m 17.5 ± 0.5a-f,h,i-m B. subtilis NRRL B-543 NAg-j,l NAg-j,l NAg-j,l NAg-j,l NAg-j,l NAg-j,l 11.53 ± 0.5a-f,h,I,k-m E. coli ATCC 25955 NAc-f,i NAc-f,i 12.33 ± 0.35 a,b,d- 13.2 ± 0.26 a-c,e,g-m 14.8 3 8.46 ± 0.45 a-c,e,g-m NAc-f,i h,j-m ± 0.47a-d,f-m S. typhimurium ATCC 14028 NAc-f NAc-f 8.0 ± 1.0 a,b,f-m 7.3 ± 0.26 a,b,f-m 8.2 ± 0.26a,b,f-m 10.5 ± 0.5 a,b,f-m NAa-e,g-m K. pneumonia ATCC 13883 NAg-j,m NAg-j,m NAg-j,m NAg-j,m NAg-j,m NAg-j,m 15.36 ± 0.40g-j,m

Micro-organism Inhibition zone (mm)

F_AU(h) F_TR(i) F_SP(j) F_NIT(k) F_VER(l) F_LS(m) Controla

A. fumigatus 22.5 NAg,h,j,m 12 NAg,h,j,m NAg,h,j,m 15.16 17 ± 0.5a-g,i-m ± 1.0 a-f,h,I,k-m ± 0.15a-l C. albicans NAc-f NAc-f NAc-f NAc-f NAc-f NAc-f 20 S. mutants 8.5 ± 0.5 a-g,i.j.I,k,m NA a,b,c,e,f,h,I,k,m NA a,b,c,e,f,h,i.I,k,m 7.43 8.16 7.43 20 a-d,f,g,h,i.I a-e,f,g,i.j a-d,f-k 267 ± 0.40 ± 0.15 ± 0.20 S. aureus 20.23 17.0 11.53 10.26 ± 0.25a-i,l,m 14.33 15.43 24 ± 0.20a-g,i-m ± 1.0a-f,j-l ± 0.55a-h,l-m ± 0.41a-k ± 0.45a-k B. subtilis 9.0 15.26 ± 0.30a-h,j-m 12.46 NAg-l 13.5 ± 0.5 a-I,k,m NAg-j,l 26 ± 1.0a-g,i-m ± 0.50 a-f,h-k,m E. coli NAc-f,i 12.3 NAc-f,i NAc-f,i NAc-f,i NAc-f,i 30 ± 0.26a,b,d-h,k-m S. typhimurium NAc-f NAc-f NAc-f NAc-f NAc-f NAc-f 17 K. pneumonia 14.26 16.6 12.53 NAg-j,m NAg-j,m 10.4 21 ± 0.20a-g,i-m ± 0.36a-h,j-m ± 0.32a-I,k-m ± 0.36a-l

Values are expresses as mean ± SD (n = 3). NA: No activity. (a–m): Different letters indicate significant differences between Ficus. Samples according to least significant difference analysis (P < 0.05; Tukey's test). The test was done using the diffusion agar technique, well diameter: 6.0 mm (100 μl was tested). Industrial Crops&Products126(2018)261–271 (F_BG) F. benghalensis L; (F_BN) F. benjamina L.; (F_MY) F.mysorensis Heyne Ex. Roth.; (F_AF) F.afzelii G. Don.; (F_PY) F. Pyriformis Hook. & Arn. H; (F_RA) F. racemosa Roxb.; (F_LU) F. lutea Vahl.; (F_AU) F.auriculata L.; (F_TR) F. trigonate L.; (F_SP) F. spragueana M.; (F_NIT) F. microcarpa var. nitida; (F_VER) F. virens A.; (F_LS) F. religiosa L. a Antimicrobial drugs used as positive control for their respective microorganisms are as follows: ketoconazole (100 μg/ml) for fungi “A. fumigatus and C. albicans”, gentamycin (4 μg/ml) for Gram positive bacteria “S. mutants, S. aureus & B. Subtilis” and Gram negative bacteria “E. coli, S. typhimurium & K. pneumonia”. S.S. Elhawary et al. Industrial Crops & Products 126 (2018) 261–271

Fig. 3. LC/MS-based unsupervised principal component analysis (PCA) and hierarchical cluster analysis of the identified metabolites in 13 Ficus spp. (A) PCA score plot of PC1 vs. PC2 scores. (B) Loading plot of PC1 vs. PC2 loadings, with the explained variance of PC1 = 41% and PC2 = 21%. (C) HCA dendrogram. (F_BG) F. benghalensis L; (F_BN) F. benjamina L. ; (F_MY) F. mysorensis Heyne Ex. Roth.; (F_AF) F. afzelii G. Don.; (F_PY) F. pyriformis Hook. & Arn H; (F_RA) F. racemosa Roxb.; (F_LU) F. lutea Vahl.; (F_AU) F. auriculata L.; (F_TR) F. trigonate L.; (F_SP) F. spragueana M.; (F_NIT) F. microcarpa var. nitida; (F_VER) F. virens A.; (F_LS) F. religiosa L.

(R2 = 0.71) and predictive power of the model (Q2 = 0.77). 2) and apigenin 8-C-xyloside-6-C-glucoside (vicenin 3) which appeared The PLS biplot (Fig. 4) showed that “F_AU” was strongly correlated to be enriched in “F_PY”. These apigenin C-diglycosides have a well with the antimicrobial activity against A. fumigatus and S. aureus with reported antimicrobial activity against E. coli (Ali and Dixit, 2012). quercetin-3-O-glucoside (isoquercitrin) being the most influential me- Besides, “F_PY” was found to possess the highest antimicrobial activity tabolites responsible for the activity. It worth noting that “F_AU” was against the previously mentioned strains among the studied Ficus the most active species against those strains as observed in the in vitro samples. antimicrobial activity. The same antimicrobial activity was recorded with “F_LU”, but at much lower potential and the contributing meta- 3.4. Study of anti-quorum sensing efficiency of some selected Ficus bolites for its activity was identified to be kaempferol hexoside rham- phytochemicals noside, hyperoside, taxifolin (dihydroquercetin) and vitexin-2”-O- rhamnoside as concluded from the biplot (Fig. 4). It is worth-noting that Bacterial infectious diseases are mediated through the proliferation quercetin-3-O-glucoside, kaempferol rhamnoside and hyperoside were of bacterial cells within quorum sensing mechanism. This signaling previously reported to have anti-S. aureus activity (Rigano et al., 2007; mechanism depends on the cell density of small signaling molecules Tatsimo et al., 2012; Umaarasu et al., 2018). called auto-inducers or bacterial pheromones play a vital role in cell to Regarding the antimicrobial of B. subtilis, K. pneumonia, it was po- cell communication and regulating the virulence factor of many food- sitively correlated with the dihydroquercetin, 5,7,8,4′-tetrahydroxy- borne pathogens. Accordingly, it is well-documented that the inter- flavanone (carthamidin), cis-5-O-p-coumaroylquinic acid, 3,4-dimethyl- ruption of quorum sensing pathway provides an attractive strategy to caffeic acid, which were more abundant in “F_TR”. These findings were combat microbial infections (Adonizio et al., 2006; Gopu et al., 2015). cohort to the results of the in vitro antimicrobial assay which showed Natural quorum sensing inhibitors obtained from fruits and vege- that “F_TR” has the highest antimicrobial activity against B. subtilis and tables can be regarded as promising sources that can potentially inhibit K. pneumonia. quorum sensing pathway involved in human pathogeneses, and hence In contrast, “F_PY” was located in the opposite side (with negative of therapeutic potential (Adonizio et al., 2006; Vattem et al., 2007; scores) of the plot, showing a negative correlation to the previously Nazzaro et al., 2013). Moreover, they have additional merits other than mentioned antimicrobial activities; however, it is positively correlated synthetic antimicrobial agents in being nontoxic inhibitors and can to the antimicrobial activity against C. albicans and E. coli. The most control infections without the emergence of bacterial resistance influential phytochemicals that contributed to these bioactivities are (Hentzer and Givskov, 2003). isoschaftoside and three apigenin C-diglycosides namely “apigenin 6-C- In silico analysis were conducted to screen the quorum sensing in- xyloside-8-C-glucoside (vicenin 1), apigenin-6,8 C-diglucoside (vicenin hibitory activity of some selected phytochemicals, viz. quercetin-3-

268 S.S. Elhawary et al. Industrial Crops & Products 126 (2018) 261–271

Fig. 4. The OPLS biplot showing the correlation of the 35 metabolites in different Ficus species (listed in Table 1) with their antimicrobial activities against 8 microbial strains; A. fumigatus, C. albicans, S. mutants, S. aureus, B. Subtilis, E. coli, S. typhimurium & K. pneumonia. (F_BG) F. benghalensis L; (F_BN) F. benjamina L.; (F_MY) F. mysorensis Heyne Ex. Roth.; (F_AF) F. afzelii G. Don.; (F_PY) F. pyriformis Hook. & Arn H.; (F_RA) F. racemosa Roxb.; (F_LU) F. lutea Vahl.; (F_AU) F.auriculeta L.; (F_TR) F. trigonate L.; (F_SP) F. spragueana M.; (F_NIT) F. mi- crocarpa var. nitida; (F_VER) F. virens A.; (F_LS) F. religiosa L.

Table 3 Docking energy scores (S) in Kcal/mol and the interactions of the LasR receptor proteins with the tested phytochemicals.

No. Compound Docking score (Kcal/ Hydrogen bonding (Distance Å) Other interactions mol)

1 TX1 −16.68 Tyr56 (2.75), Asp73(2.90) Trp88, Phe101, Ala105 and Ser129 (3.12) (hydrophobic interaction) 2 Quercetin-3-glucoside −21.94 Asp65 (2.89) and Ser129 (2.70) Tyr64 (π-π stacking) 3 Kaempferol-3-O-rutinoside −26.83 Thr75(2.62) and Ser129 (2.55) (2.69) Tyr64 (π-π stacking) 4 Kaempferol-3-O-glucoside −21.59 Asp65 (2.87) and Ser129 (2.70) Tyr64 (π-π stacking) 5 Rutin −25.20 Thr75(3.00), Leu110 (2.56) and Ser129 (2.52) (3.13) – 6 Chlorogenic acid −17.12 Tyr47 (2.92), Trp60 (2.58), Asp65 (2.93), Ser129 (2.55) (2.92) and Leu36 and Ile52 (hydrophobic interaction) Thr115 (2.85)

glucoside, kaempferol-3-O-rutinoside, kaempferol-3-O-glucoside, rutin ethanolic extracts of 13 Ficus spp., which were tentatively identified, for and chlorogenic acid, identified in Ficus species (F. AU) that showed the the first time, using HPLC-ESI-MS/MS and belonged to different classes most promising in vitro antimicrobial activity. The hotspot residue of including flavonoids viz. flavonols, flavanols, flavanonols, flavones and the protein molecule and the changes in the protein conformation due flavanones, and flavonolignans, anthocyanins and hydroxycinnamic to the interaction with the signaling molecule (TX1) and the tested acids and derivatives. phytochemicals were identified. The study also highlighted the potency of some of the studied Ficus The ability of the tested phytochemicals to interact with the key species namely “F. auriculata, F. lutea Vahl. and F. trigonata L.” as pos- amino acids through H-bonding with Tyr56, Asp73 and Ser129 in the sessing natural antimicrobial potentiality and could provide a source binding site of LasR receptor rationalizes their efficiency as quorum for developing novel natural antimicrobial agents. sensing inhibitory activity as indicated by their docking pattern and Potential natural quorum sensing inhibitors viz. quercetin-3-gluco- docking score with LasR receptor protein compared to that of TX1 (ca. side, kaempferol-3-O-rutinoside, kaempferol-3-O-glucoside, rutin and −16.68 Kcal/mol), with kaempferol-3-O-rutinoside and rutin being the chlorogenic acid were identified in the current study which might most potent inhibitors, depicted (Table 3 and Fig. 5). Accordingly, it provide effective management of bacterial infections and also enhance can be concluded that these Ficus phytochemicals can serve as novel the food safety. quorum sensing inhibitors to manage human and food borne pathogens. Future work is recommended to be performed for the isolation and purification of the active compounds from Ficus species with the most 4. Conclusion promising antimicrobial and anti-quorum sensing activity. Moreover, in vivo testing and clinical studies are yet to be conducted to support our In the present study, we characterized 35 phytochemicals in findings and to approve the proposed phytochemicals as safe

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Fig. 5. Results of molecular docking study of the quorum sensing inhibitory activity of some selected Ficus phytochemicals, A: 2D interaction diagram showing TX1 docking pose interactions with the key amino acids in the LasR binding site; B1 & B2: 2D representation and 3D representation of the superimposition of the co- crystallized (red) and the docking pose (blue) of TX1 in the LasR binding site with RMSD of 0.798 Å. (Ligand Hydrogen atoms were removed for clarity); C: 2D diagram of quercetin-3-glucoside in the LasR binding site; D: 2D diagram of Kaempferol-3-O-rutinoside in the LasR binding site; E: 2D diagram of compound kaempferol-3-O-glucoside in the LasR binding site. F: 2D diagram of rutin in the LasR binding site; G: 2D diagram of chlorogenic acid in the LasR binding site.

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